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We establish a new connection between moments of $n \times n$ random matrices $X_n$ and hypergeometric orthogonal polynomials. Specifically, we consider moments $\mathbb{E}\mathrm{Tr} X_n^{-s}$ as a function of the complex variable $s \in…

Mathematical Physics · Physics 2019-07-23 Fabio Deelan Cunden , Francesco Mezzadri , Neil O'Connell , Nick Simm

In the setting of polynomial jump-diffusion dynamics, we provide an explicit formula for computing correlators, namely, cross-moments of the process at different time points along its path. The formula appears as a linear combination of…

Probability · Mathematics 2021-04-26 Fred Espen Benth , Silvia Lavagnini

We study the real eigenvalue statistics of products of independent real Ginibre random matrices. These are matrices all of whose entries are real i.i.d. standard Gaussian random variables. For such product ensembles, we demonstrate the…

Probability · Mathematics 2021-09-02 Will FitzGerald , Nick Simm

In this paper we address the complexity of solving linear programming problems with a set of differential equations that converge to a fixed point that represents the optimal solution. Assuming a probabilistic model, where the inputs are…

Computational Complexity · Computer Science 2007-05-23 Asa Ben-Hur , Joshua Feinberg , Shmuel Fishman , Hava T. Siegelmann

We consider a complex-valued linear mixture model, under discrete weakly stationary processes. We recover latent components of interest, which have undergone a linear mixing. We study asymptotic properties of a classical unmixing estimator,…

Statistics Theory · Mathematics 2020-03-12 Niko Lietzén , Lauri Viitasaari , Pauliina Ilmonen

Akemann, Ipsen, and Kieburg showed recently that the squared singular values of a product of M complex Ginibre matrices are distributed according to a determinantal point process. We introduce the notion of a polynomial ensemble and show…

Probability · Mathematics 2015-01-20 Arno B. J. Kuijlaars , Dries Stivigny

We consider the product of n complex non-Hermitian, independent random matrices, each of size NxN with independent identically distributed Gaussian entries (Ginibre matrices). The joint probability distribution of the complex eigenvalues of…

Mathematical Physics · Physics 2015-06-11 G. Akemann , Z. Burda

We impose the uniform probability measure on the set of all discrete Gelfand-Tsetlin patterns of depth $n$ with the particles on row $n$ in deterministic positions. These systems equivalently describe a broad class of random tilings models,…

Probability · Mathematics 2018-07-03 Erik Duse , Anthony Metcalfe

We introduce and study a class of discrete particle ensembles that naturally arise in connection with classical random matrix ensembles, log-gases and Jack polynomials. Under technical assumptions on a general analytic potential we prove…

Probability · Mathematics 2022-07-20 Evgeni Dimitrov , Alisa Knizel

In this work we consider time series with a finite number of discrete point changes. We assume that the data in each segment follows a different probability density functions (pdf). We focus on the case where the data in all segments are…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Ali Mohammad-Djafari , Olivier Feron

A discrete model of Brownian sticky flows on the unit circle is described: it is constructed with products of Beta matrices on the discrete torus. Sticky flows are defined by their ``moments'' which are consistent systems of transition…

Probability · Mathematics 2007-05-23 Yves Le Jan , Sophie Lemaire

The paper deals with the convergence properties of the products of random (row-)stochastic matrices. The limiting behavior of such products is studied from a dynamical system point of view. In particular, by appropriately defining a dynamic…

Probability · Mathematics 2013-01-15 Behrouz Touri , Angelia Nedich

The unitary group with the Haar probability measure is called Circular Unitary Ensemble. All the eigenvalues lie on the unit circle in the complex plane and they can be regarded as a determinantal point process on $\mathbb{S}^1$. It is also…

Probability · Mathematics 2022-03-16 Makoto Katori , Tomoyuki Shirai

We introduce a theory of probability in $\lambda$-rings designed to efficiently describe random variables valued in multisets of complex numbers, varieties over a field, or other similar enriched settings. A key role is played by the…

Number Theory · Mathematics 2025-06-10 Sean Howe

We study a 2-parametric family of probability measures on the space of countable point configurations on the punctured real line (the points of the random configuration are concentrated near zero). These measures (or, equivalently, point…

Representation Theory · Mathematics 2007-05-23 Alexei Borodin

We study the behavior of two-time correlation functions at late times for finite system sizes considering observables whose (one-point) average value does not depend on energy. In the long time limit, we show that such correlation functions…

Statistical Mechanics · Physics 2025-08-20 Oscar Bouverot-Dupuis , Silvia Pappalardi , Jorge Kurchan , Anatoli Polkovnikov , Laura Foini

We distinguish a class of random point processes which we call Giambelli compatible point processes. Our definition was partly inspired by determinantal identities for averages of products and ratios of characteristic polynomials for random…

Mathematical Physics · Physics 2007-05-23 Alexei Borodin , Grigori Olshanski , Eugene Strahov

The ensemble inter-relations to be considered are special features of classical cases, where the joint eigenvalue probability density can be computed explicitly. Attention will be focussed too on the consequences of these inter-relations,…

Mathematical Physics · Physics 2024-09-04 Peter J. Forrester

We introduce a space inhomogeneous generalization of the dynamics on interlacing arrays considered by Borodin and Ferrari. We show that for a certain class of initial conditions the point process associated to the dynamics has determinantal…

Probability · Mathematics 2020-03-18 Theodoros Assiotis

We study the distribution of singular values of product of random matrices pertinent to the analysis of deep neural networks. The matrices resemble the product of the sample covariance matrices, however, an important difference is that the…

Mathematical Physics · Physics 2022-07-05 L. Pastur , V. Slavin